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Post‐implant computed tomography–magnetic resonance prostate image registration using feature line parallelization and normalized mutual information

机译:植入后计算机体层摄影术-使用特征线平行化和归一化互信息的磁共振前列腺图像配准

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摘要

Post‐implant dosimetry for permanent prostate brachytherapy is typically performed using computed tomography (CT) images, for which the clear visualization of soft tissue structures is problematic. Registration of CT and magnetic resonance (MR) image volumes can improve the definition of all structures of interest (soft tissues, bones, and seeds) in the joint image set. In the present paper, we describe a novel two‐stage rigid‐body registration algorithm that consists of (1) parallelization of straight lines fit to image features running primarily in the superior–inferior (Z) direction, followed by (2) normalized mutual information registration. The first stage serves to fix rotation angles about the anterior–posterior (Y) and left–right (X) directions, and the second stage determines the remaining Z‐axis rotation angle and the X, Y, Z translation values. The new algorithm was applied to CT and 1.5T MR (T2‐weighted and balanced fast‐field echo sequences) axial image sets for three patients acquired four weeks after prostate brachytherapy using I125 seeds. Image features used for the stage 1 parallelization were seed trains in CT and needle tracks and seed voids in MR. Simulated datasets were also created to further investigate algorithm performance. Clinical image volumes were successfully registered using the two‐stage approach to within a root‐mean‐squares (RMS) distance of <1.5 mm, provided that some pubic bone and anterior rectum were included in the registration volume of interest and that no motion artifact was apparent. This level of accuracy is comparable to that obtained for the same clinical datasets using the Procrustes algorithm. Unlike Procrustes, the new algorithm can be almost fully automated, and hence we conclude that its further development for application in post‐implant dosimetry is warranted.PACS numbers: 87.53.Jw, 87.57.Gg, 87.59.Fm, 87.61.Pk
机译:永久性前列腺近距离放射治疗的植入后剂量测定通常使用计算机断层扫描(CT)图像进行,对于这些图像,软组织结构的清晰可视化是有问题的。 CT和磁共振(MR)图像体积的配准可以改善关节图像集中所有感兴趣的结构(软组织,骨骼和种子)的清晰度。在本文中,我们描述了一种新颖的两阶段刚体配准算法,该算法包括(1)拟合主要沿上下(Z)方向运行的图像特征的直线平行化,然后是(2)归一化互信息注册。第一阶段用于固定前后(Y)和左右(X)方向的旋转角度,第二阶段确定剩余的Z轴旋转角度和X,Y,Z平移值。这项新算法被用于CT和1.5T MR(T2加权和平衡快速场回波序列)轴向图像集,用于三名前列腺近距离放射治疗后四周后使用 I 125 种子。用于阶段1并行化的图像特征是CT中的种子列和MR中的针迹以及种子空隙。还创建了模拟数据集,以进一步研究算法性能。使用两阶段方法成功注册临床图像量,以均方根(RMS)距离<1.5 mm为前提,前提是感兴趣的注册量中包括一些耻骨和前直肠并且没有运动伪影很明显。该准确性水平与使用Procrustes算法获得的相同临床数据集的准确性相当。与Procrustes不同,新算法几乎可以完全自动化,因此我们得出结论,有必要对其进行进一步开发,以用于植入后剂量测定.PACS编号:87.53.Jw,87.57.Gg,87.59.Fm,87.61.Pk

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